Data Scientist: Financial Crime Risk Management
5 days ago
As a key member of our team, you will be responsible for developing, implementing, and maintaining next-generation Artificial Intelligence (AI) and Machine Learning (ML) models to mitigate financial crime risks using advanced analytics across the organization.
We are looking for an experienced professional with hands-on expertise in AFC/sanctions analytics and compliance roles. The ideal candidate will have strong analytical and problem-solving skills, with the ability to think strategically and make data-driven decisions.
The successful candidate will collaborate with stakeholders to develop predictive models, blockchain analytics, generative AI models, and AI-driven behavioral analytics to identify financial crime risks. They will analyze transactional data to identify anomalies and patterns indicative of financial crime, and support the enhancement of existing monitoring systems and tools to improve detection efficiency and reduce false positives.
The role requires a Bachelor's degree in Data Science, Statistics, Finance, Business Administration, Computer Science, or a related field, and minimum of 6-8 years in the financial services industry. Experience with big data analytics tools and frameworks, including Hive, Spark, and Impala, is desirable but not required.
The successful candidate will be able to communicate complex ideas effectively, and work collaboratively with cross-functional teams. In-depth understanding of AML/CFT regulations, transaction monitoring systems, and anti-financial crime compliance best practices is essential for this role.
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